loklak

As elastic.io mentions, Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. But in many setups, it is not possible to manually install an Elasticsearch node on a machine. To handle these type of scenarios, Elasticsearch provides the NodeBuilder module, which can be used to spawn Elasticsearch node programmatically. Let's see how. Getting Dependencies In order to get the ES Java API, we need to add the following line to dependencies. compile group: 'org.elasticsearch', name: 'securesm', version: '1.0' The required packages will be fetched the next time we gradle build. Configuring Settings In the Elasticsearch Java API, Settings are used to configure the node(s). To create a node, we first need to define its properties. Settings.Builder settings = new Settings.Builder(); settings.put("cluster.name", "cluster_name"); // The name of the cluster // Configuring HTTP details settings.put("http.enabled", "true"); settings.put("http.cors.enabled", "true"); settings.put("http.cors.allow-origin", "https?:\/\/localhost(:[0-9]+)?/"); // Allow requests from localhost settings.put("http.port", "9200"); // Configuring TCP and host settings.put("transport.tcp.port", "9300"); settings.put("network.host", "localhost"); // Configuring node details settings.put("node.data", "true"); settings.put("node.master", "true"); // Configuring index settings.put("index.number_of_shards", "8"); settings.put("index.number_of_replicas", "2"); settings.put("index.refresh_interval", "10s"); settings.put("index.max_result_window", "10000"); // Defining paths settings.put("path.conf", "/path/to/conf/"); settings.put("path.data", "/path/to/data/"); settings.put("path.home", "/path/to/data/"); settings.build(); // Buid with the assigned configurations There are many more settings that can be tuned in order to get desired node configuration. Building the Node and Getting Clients The Java API makes it very simple to launch an Elasticsearch node. This example will make use of settings that we just built. Node elasticsearchNode = NodeBuilder.nodeBuilder().local(false).settings(settings).node(); A piece of cake. Isn't it? Let's get a client now, on which we can execute our queries. Client elasticsearhClient = elasticsearchNode.client(); Shutting Down the Node elasticsearchNode.close(); A nice implementation of using the module can be seen at ElasticsearchClient.java in the loklak project. It uses the settings from a configuration file and builds the node using it. Visualisation using elasticsearch-head So by now, we have an Elasticsearch client which is capable of doing all sorts of operations on the node. But how do we visualise the data that is being stored? Writing code and running it every time to check results is a lengthy thing to do and significantly slows down development/debugging cycle. To overcome this, we have a web frontend called elasticsearch-head which lets us execute Elasticsearch queries and monitor the cluster. To run elasticsearch-head, we first need to have grunt-cli installed - $ sudo npm install -g grunt-cli Next, we will clone the repository using git and install dependencies - $ git clone git://github.com/mobz/elasticsearch-head.git $ cd elasticsearch-head $ npm install Next, we simply need to run the server and go to indicated address on a web browser - $ grunt server At the top, enter the location at which elasticsearch-head can interact with the cluster and Connect. Upon connecting, the dashboard appears telling about the status of cluster - The dashboard shown above is from the loklak project (will talk more about it). There are 5 major sections in the UI - 1. Overview: The above screenshot, gives details about the indices and shards of the cluster.…